The actual grammar used
to generate sentences that the models were trained on deviated
slightly from that reported in the article. Specifically,
on benefactive datves with non-light verbs, the grammar generated
sentences always without goal arguments. The following sections
of the article are impacted:

pg. 628-629. About half of the dog-goal test items used the
benefactive datives structures with DOG in the goal role.
Because this meaning was associated with a two argument transitive
structure (without the phrase that included the word "dog"),
this test probably overestimated the ability of the models
to produce this novel prepositional phrases with the word
"dog". Another test set (the overt-dog-goal test
set) was created made up of sentences with DOG in the goal
slot, and a structure where the word "dog" was overtly
produced. When tested in same manner as the original dog-goal
test, the results are on the whole similar (Prod-SRN 0%, No-event-semantics
model 18%, Linked-path model 36%, Dual-path model 60%). Model
type is significant [F(3,9) = 12.0, p < 0.002]. Pairwise
comparisons demonstrate that the Dual-path model is superior
to the Prod-SRN and No-event-semantics models [Fs(1,9) >
16.3, ps < 0.003] and marginally superior to the Linked-path
model [F(1,9) = 5.1, p < 0.06]. These results, in concert
with the original dog-goal results, suggest that the Dual-path
model is better at placing words into novel sentence positions.

None of the substantive conclusions of the study are affected
by these changes.